libAtoms/matscipy

Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials Project.

atomate2 is a library of computational materials science workflows

Torch-native, batchable, atomistic simulations.

An open-source Python package for creating fast and accurate interatomic potentials.

Universal machine-learning models for advanced atomistic simulations

Powerful, efficient particle trajectory analysis in scientific Python.

A toolkit for visualizations in materials informatics.

Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov

Graph deep learning library for materials